nm000224 NEMAR-native dataset
Imagined speech EEG dataset — short and long words (Nguyen et al. 2017)
This dataset comprises preprocessed EEG recordings from 6 healthy participants performing imagined speech discrimination tasks between short and long words ('cooperate' vs 'in'). Data were acquired at 256 Hz using 64 EEG channels with standard preprocessing including bandpass filtering (8-70 Hz), notch filtering (60 Hz), and artifact removal. The dataset contains 1,200 trials analyzed using Riemannian manifold and relevance vector machine approaches for brain-computer interface applications, achieving mean classification accuracy of 73.3±8.9%.
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Coming soon. Per-file data-quality summaries are precomputed by the NEMAR processing pipeline. The static aggregate is on the way — tracked at nemar-cli#511.